VNN3 is a potential novel biomarker for predicting prognosis in clear cell renal cell carcinoma

Anim Cells Syst (Seoul). 2019 Mar 1;23(2):112-117. doi: 10.1080/19768354.2019.1583126. eCollection 2019 Apr.

Abstract

Although pathological observations provide approximate prognoses, it is difficult to achieve prognosis in patients with existing prognostic factors. Therefore, it is very important to find appropriate biomarkers to achieve accurate cancer prognosis. Renal cell carcinoma (RCC) has several subtypes, the discrimination of which is crucial for proper treatment. Here, we present a novel biomarker, VNN3, which is used to prognose clear cell renal cell carcinoma (ccRCC), the most common and aggressive subtype of kidney cancer. Patient information analyzed in our study was extracted from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts. VNN3 expression was considerably higher in stages III and IV than in stages I and II. Moreover, Kaplan-Meier curves associated high VNN3 expression with poor prognoses (TCGA, p < .0001; ICGC, p = .00076), confirming that ccRCC prognosis can be predicted via VNN3 expression patterns. Consistent with all patient results, the prognosis of patients with higher VNN3 expression was worse in both low stage (I and II) and high stage (III and IV) (TCGA, p < 0.0001 in stage I and II; ICGC, p = 0.028 in stage I and II; TCGA, p = 0.005 in stage III and IV). Area under the curve and receiver operating characteristic curves supported our results that highlighted VNN3 expression as a suitable ccRCC biomarker. Multivariate analysis also verified the prognostic performance of VNN3 expression (TCGA, p < .001; ICGC, p = .017). Altogether, we suggest that VNN3 is applicable as a new biomarker to establish prognosis in patients with ccRCC.

Keywords: ICGC; TCGA; VNN3; biomarker; clear cell renal cell carcinoma.

Grants and funding

This study was supported by grants from the Basic Science Research Program (MOE, NRF-2016R1A6A3A11931738; 2016R1D1A1B03934716) and Collaborative Genome Program for Fostering New Post-Genome Industry (NRF-2017M3C9A6047610) through the National Research Foundation of Korea (NRF) grant funded by the Korean government.